1. Field of the Invention
The present invention relates generally to a method, apparatus, and product for real-time predictive time-to-completion for variable configure-to-order manufacturing.
2. Description of the Related Art
When products are “built to customer order” there is often substantial variability in the products being produced, even within different configurations of a single product. A product can be configured in many different ways. For example, a customer could choose to order a product. The customer would then select the options that the customer is interested in having included in the customer's particular configuration of the product. These options could include different memory types/sizes/speeds, different storage devices, different processors, etc. In computer products, this variability can be many combinations of hardware, software, and instructional features. The effect of this variability is significant time differences in the processes (such as kitting, build, test, and software preload) used to manufacture the configuration of a product that a customer ordered.
Manufacturing historically uses average cycle times, referred to herein as “historical cycle times”. A cycle time is the amount of time it takes for a manufacturing activity to be completed. A few examples of manufacturing activities include: power up with built-in self tests, wait for all resources to report in; checking microcode levels; surface scan of hard drives; start up/halting of exercises; configuring of hardware, such as enabling redundancy of hard drive arrays; and loading of software images.
The historical cycle time for an activity is determined over a course of time during which the activity was performed for many different configurations of a product. Thus, the historical cycle time is not determined on an order-by-order basis. It represents an average that was determined by taking the time it took to complete the activity for all ordered configurations of a product that required this activity divided by the number of times that the activity was completed.
FIG. 8 depicts a calculation of a historical cycle time for an activity in accordance with the prior art. The process starts as illustrated by block 800 and passes to block 802 which depicts, for all ordered configurations of a particular product, monitoring the time it takes to complete an activity. Next, block 804 illustrates calculating the average time it took to complete the activity. The average time is calculated by adding together the time it took to complete the activity for each ordered configuration, and then dividing the total time by the number of times the activity was completed. The process then terminates as depicted by block 806.
Automated solutions that predict order completion times, which utilize time estimates for each operation, assume a “typical” configuration. Configuration variations of a product are not factored in. Due to the huge variability within each product, it is not practical to develop estimates for every possible configuration. Because the estimates are not reliable on an order-by-order basis, the estimates are either not used or, worse yet, prompt incorrect decisions.
Manual solutions to interrogate each ordered configuration during the production activities is labor intensive and error prone. It is nearly impossible to synthesize the data to make accurate projections, and expert skills are required to perform this analysis. These are the same skills required to support production. Using the expert skills to make projections drives inefficiency in manufacturing, making the situation worse.
Therefore, known automated solutions for predicting a completion time for completing the manufacturing of an ordered configuration of a product use the historical cycle times. FIG. 9 illustrates estimating the amount of time it will take to manufacture the particular configuration of a product that has been ordered in accordance with the prior art. The process starts as depicted by block 900 and then passes to block 902 which illustrates receiving an order to manufacture a particular configuration of a product. Thereafter, block 904 depicts identifying the activities that are necessary to manufacture the ordered configuration. Next, block 906 illustrates retrieving the historical cycle times for each identified activity. Block 908 then depicts estimating the amount of time it will take to manufacture the ordered configuration by adding together the historical cycle times for each identified activity. The process then terminates as illustrated by block 910.
FIG. 10 depicts the calculation of the predicted completion time in accordance with the prior art. Prior to completing any activity, the predicted completion time that an ordered configuration of a product will be completely manufactured is equal to the sum of the historical cycle times for each activity. After completing an activity, the predicted completion time is equal to the historical cycle times of the remaining activities.
Because the known automated solutions assume a “typical” configuration of a product, the automated solutions do not provide an accurate prediction of the time it will take to completely manufacture an ordered configuration of a product. FIG. 11 is a table that lists the historical cycle times for each of a plurality of activities as well as the actual cycle times for two different configurations, configuration A and configuration B, of a particular product, 9406 570.
Using the historical cycle times, the known solutions will predict that it will take 254.5 units of time to manufacture product 9406 570. This prediction may not be very accurate for the configurations of the product that are actually ordered, however. For example, a “light” configuration of the product might be ordered. As depicted by FIG. 11, it would take only 220.7 units of time to manufacture the “light” configuration. Alternatively, a “heavy” configuration might be ordered. It would take 495.4 units of time to manufacture the “heavy” configuration.
Several different factors contribute to the variability in the time it takes to manufacture a configuration of a product. For example, for computer systems, the quantity and size of the memory; the capacity, speed, and quantity of the storage devices; the number and speed of the processors; the quantity and type of the I/O adapters; and the physical placement of all of the components in the physical enclosures determine the amount of time a particular configuration of product will require for manufacturing.
The “light” and “heavy” configurations are different configurations of the same product. Because an average is used to predict the manufacturing times for each activity, the predicted completion time will not be accurate for either the “light” or “heavy” configuration.
The historical cycle times are estimates that are based on the manufacturing history of multiple different ordered configurations. These orders might have included “light” configurations, “heavy” configurations, or, most probably, a combination of both types of configurations. Because these are averages, they cannot be used to accurately predict the manufacturing times of individual orders.